Az adatok hatalma

Arató Bence

BI Consulting

Ügyvezető igazgató

3

Kettős kihívás

Source: "What's your data strategy?" HBR May-June 2017

Technológia

Dresner Advisory Services - Big Data Analytics Market Study 2017

2018

Gartner 208 Magic Quadrant for Data Management Solutions for Analytics Gartner Magic Quadrant for Data Management Solutions for Analytics, February 2018

2018

Gartner 208 Magic Quadrant for Data Management Solutions for Analytics Gartner Magic Quadrant for Data Management Solutions for Analytics, February 2018

„The leading 2017 story of Hadoop distributions is that nobody seems to want to be accused of being in the business of providing them”

Merv Adrian, Gartner

https://blogs.gartner.com/merv-adrian/2017/12/29/december-2017-tracker-wheres-hadoop

Gartner 2017 Hype Cycle for Data Management

Vendor transformation

Vendor transformation

blogs.gartner.com/merv-adrian/2017/12/29/december-2017-tracker-wheres-hadoop

Qubole 2018 Big Data Activation Report

Qubole 2018 Big Data Activation Report

Pénzügyi eredmények

Hortonworks

Hortonworks

Cloudera

Source: Forbes

Cloudera

Cloudera

AI kihívások

AI Hype

Source: Gergely Daróczi

blog.openai.com/ai-and-compute

blog.openai.com/ai-and-compute

blog.openai.com/ai-and-compute

www.extremetech.com/extreme/269008-google-announces-8x-faster-tpu-3-0-for-ai-machine-learning

vectordash.com

2017

index.hu/tech/2017/01/03/magyarorszagot_is_elfoglaljak_a_csevegobotok

2017

index.hu/kultur/media/2017/01/03/robotizaltuk_az_indexet

2018

index.hu/tech/2018/06/07/a_forradalom_erdeklodes_hianyaban_elmaradt

Hazai helyzet

Hungarian Cluster Showcase

Hungarian Cluster Showcase

Central Média

IBM Budapest Lab Prezi

Node 12 10 41 CPU 96 320 168 Memória 384 GB 600 GB 672 GB Adatmennyiség 15 TB 800 TB 1 PB+ Tárolás S3 S3 Hadoop Cloudera EMR EMR SQL motor Impala Hive, Spark, Presto Presto, Spark, Hive Devops (fő) 2 3 3 User (fő) 8 20 90

Hungarian Cluster Showcase

Magyar Telekom

Mol group

Telenor Hungary

Node 26 6 15 CPU 500 48 30 Memória 4500 GB 384 GB 3800 GB Adatmennyiség 400 TB 24TB 50 TB Tárolás Clusteren Clusteren Clusteren Hadoop Cloudera Cloudera Cloudera

SQL motor Hive, Spark,

Impala Hive, Spark,

Impala Spark

Devops (fő) 30 10 10 User (fő) 500 30 20

Source: Cloudera

www.nng.com/hanagyleszek

www.nng.com/hanagyleszek

www.nng.com/hanagyleszek

GDPR

Source:Hortonworks

(viber)

https://www.facebook.com/photo.php?fbid=10204856278523793&set=gm.2086132085003351